CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

An Integrated Approach to Support Knowledge Representation, Sharing and Perception over Web2.0

by Iyad Al Agha
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 97 - Number 9
Year of Publication: 2014
Authors: Iyad Al Agha
10.5120/17034-7335

Iyad Al Agha . An Integrated Approach to Support Knowledge Representation, Sharing and Perception over Web2.0. International Journal of Computer Applications. 97, 9 ( July 2014), 15-24. DOI=10.5120/17034-7335

@article{ 10.5120/17034-7335,
author = { Iyad Al Agha },
title = { An Integrated Approach to Support Knowledge Representation, Sharing and Perception over Web2.0 },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 97 },
number = { 9 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 15-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume97/number9/17034-7335/ },
doi = { 10.5120/17034-7335 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:23:38.859078+05:30
%A Iyad Al Agha
%T An Integrated Approach to Support Knowledge Representation, Sharing and Perception over Web2.0
%J International Journal of Computer Applications
%@ 0975-8887
%V 97
%N 9
%P 15-24
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web 2. 0 technologies provide the communication medium which allows collaborators to share and communicate ideas. These technologies, however, exhibit limited support for knowledge transfer which is more than a communication problem. It is still unclear how people can communicate, over the Web 2. 0, cognitive activities which they undertake during the knowledge acquisition process. In this work, we present an integrated approach for knowledge sharing that addresses the needs of both knowledge providers and recipients. It combines both concept mapping and dynamic annotation to enable for effective construction and perception of knowledge. The approach begins by helping knowledge providers visualize their own experience using a tool we named "MindGate". Afterwards, an Ontology-based model is used to convert the visual representation of knowledge to a machine-readable format. This format can then be published and reused by Internet users through a prototype social network called "SocialMinds". We have tested our approach with three research students who used our approach to carry out research tasks. The analysis of user behavior, activity and tool usage proved the potential of our approach to facilitate knowledge sharing and support both individual and group work.

References
  1. Argote, L. and P. Ingram, Knowledge transfer: A basis for competitive advantage in firms. Organizational behavior and human decision processes, 2000. 82(1): p. 150-169.
  2. Wiig, K. M. , What future knowledge management users may expect. Journal of knowledge management, 1999. 3(2): p. 155-166.
  3. Szulanski, G. , The process of knowledge transfer: A diachronic analysis of stickiness. Organizational behavior and human decision processes, 2000. 82(1): p. 9-27.
  4. Kogut, B. and U. Zander, Knowledge of the firm, combinative capabilities, and the replication of technology. Organization science, 1992. 3(3): p. 383-397.
  5. Paroutis, S. and A. Al Saleh, Determinants of knowledge sharing using Web 2. 0 technologies. Journal of knowledge management, 2009. 13(4): p. 52-63.
  6. Chi, E. H. , The Social Web: Research and Opportunities. IEEE Computer, 2008. 41(9): p. 88-91.
  7. Hollan, J. , E. Hutchins, and D. Kirsh, Distributed cognition: toward a new foundation for human-computer interaction research. ACM Transactions on Computer-Human Interaction (TOCHI), 2000. 7(2): p. 174-196.
  8. Hendriks, P. , Why share knowledge? The influence of ICT on the motivation for knowledge sharing. Knowledge and process management, 1999. 6(2): p. 91-100.
  9. Hew, K. F. , Knowledge sharing among professionals in three online communities. 2006: ProQuest.
  10. Tuomi, I. Data is more than knowledge: implications of the reversed knowledge hierarchy for knowledge management and organizational memory. in System Sciences, 1999. HICSS-32. Proceedings of the 32nd Annual Hawaii International Conference on. 1999: IEEE.
  11. Bukowitz, W. R. , R. L. Williams, and F. Times, The knowledge management fieldbook. 1999: Financial Times Prentice Hall.
  12. Sowa, J. F. , Knowledge representation: logical, philosophical, and computational foundations. Vol. 13. 2000: MIT Press.
  13. Berners-Lee, T. , J. Hendler, and O. Lassila, The semantic web. Scientific american, 2001. 284(5): p. 28-37.
  14. Buzan, T. and B. Buzan, The mind map book. 2000: BBC.
  15. Eppler, M. J. , Making knowledge visible through knowledge maps: concepts, elements, cases. Handbook on knowledge management, 2003. 1: p. 189-205.
  16. Adodo, S. , Effect of Mind-Mapping as a Self-Regulated Learning Strategy on Students Achievement in Basic Science and Technology. Mediterranean Journal of Social Sciences, 2013. 4(6): p. 163.
  17. Eppler, M. J. , A comparison between concept maps, mind maps, conceptual diagrams, and visual metaphors as complementary tools for knowledge construction and sharing. Information Visualization, 2006. 5(3): p. 202-210.
  18. Huff, A. S. and M. Jenkins, Mapping strategic knowledge. 2002: SAGE Publications Limited.
  19. Coyne, R. , Designing information technology in the postmodern age: From method to metaphor. 1995: Mit Press.
  20. Gouli, E. , et al. COMPASS: an adaptive web-based concept map assessment tool. in Proceedings of the first international conference on concept mapping. 2004.
  21. Novak, J. D. and A. J. Cannas, The origins of the concept mapping tool and the continuing evolution of the tool. Information Visualization, 2006. 5(3): p. 175-184.
  22. AlAgha, I. , KnowledgePuzzle: A Browsing Tool to Adapt the Web Navigation Process to the Learner's Mental Model. Educational Technology & Society, 2012. 15(3): p. 275-287.
  23. Cannas, A. J. , et al. CmapTools: A knowledge modeling and sharing environment. in Concept maps: Theory, methodology, technology. Proceedings of the first international conference on concept mapping. 2004.
  24. Selvin, A. , et al. , Compendium: Making meetings into knowledge events. 2001.
  25. Hwang, G. -J. , Y. -R. Shi, and H. -C. Chu, A concept map approach to developing collaborative Mindtools for context-aware ubiquitous learning. British Journal of Educational Technology, 2011. 42(5): p. 778-789.
  26. Mancini, C. and S. J. Buckingham Shum, Modelling discourse in contested domains: A semiotic and cognitive framework. International Journal of Human-Computer Studies, 2006. 64(11): p. 1154-1171.
  27. Uren, V. , et al. , Semantic annotation for knowledge management: Requirements and a survey of the state of the art. Web Semantics: science, services and agents on the World Wide Web, 2006. 4(1): p. 14-28.
  28. Hillmann, D. , Using Dublin Core, 2001. URL http://dublincore. org/documents/2001/04/12/usageguide/. DCMI Recommendation, 2001.
  29. Hwang, W. -Y. and G. -L. Hsu, The effects of pre-reading and sharing mechanisms on learning with the use of annotations. TOJET, 2011. 10(2).
  30. Marshall, C. C. and A. B. Brush. Exploring the relationship between personal and public annotations. in Digital Libraries, 2004. Proceedings of the 2004 Joint ACM/IEEE Conference on. 2004: IEEE.
  31. Su, A. , et al. , A Web 2. 0-based collaborative annotation system for enhancing knowledge sharing in collaborative learning environments. Computers & Education, 2010. 55(2): p. 752-766.
  32. Cress, U. , C. Held, and J. Kimmerle, The collective knowledge of social tags: Direct and indirect influences on navigation, learning, and information processing. Computers & Education, 2012.
  33. Oren, E. , et al. , What are semantic annotations. Relatório técnico. DERI Galway, 2006.
  34. Jung, J. J. , Consensus-based evaluation framework for distributed information retrieval systems. Knowledge and Information Systems, 2009. 18(2): p. 199-211.
  35. Wang, Z. , Q. Wang, and D. -W. Wang, Bayesian network based business information retrieval model. Knowledge and Information Systems, 2009. 20(1): p. 63-79.
  36. Wang, P. , et al. , Using Wikipedia knowledge to improve text classification. Knowledge and Information Systems, 2009. 19(3): p. 265-281.
  37. Wong, T. -L. and W. Lam, Learning to extract and summarize hot item features from multiple auction web sites. Knowledge and Information Systems, 2008. 14(2): p. 143-160.
Index Terms

Computer Science
Information Sciences

Keywords

Knowledge representation Semantic Web Ontology Collaborative Learning

Powered by PhDFocusTM